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Stability for the mix-delayed Cohen-Grossberg neural networks with nonlinear impulse

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Abstract

In this paper, the authors are concerned with the stability of the mix-delayed Cohen-Grossberg neural networks with nonlinear impulse by the nonsmooth analysis. Some novel sufficient conditions are obtained for the existence and the globally asymptotic stability of the unique equilibrium point, which include the well-known results on some impulsive systems and non-impulsive systems as its particular cases. The authores also analyze the globally exponential stability of the equilibrium point. Two examples are exploited to illustrate the feasibility and effectiveness of our results.

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Authors and Affiliations

  1. Department of Dynamics and Control, Beijing University of Aeronautics and Astronautics, Beijing, 100191, China

    Yong Zhao & Qishao Lu

  2. Department of Mathematics, University of Texas-Pan American, Edinburg, TX, 78539, USA

    Zhaosheng Feng

Authors
  1. Yong Zhao
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  2. Qishao Lu
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  3. Zhaosheng Feng
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Corresponding author

Correspondence to Zhaosheng Feng.

Additional information

This research is supported by the National Natural Science Foundation of China under Grant No. 10872014, the Natural Science Foundation of Fujian Province of China under Grant No. S0750008, and partially supported by UTPA Faculty Research Council under Grant No. 119100.

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Zhao, Y., Lu, Q. & Feng, Z. Stability for the mix-delayed Cohen-Grossberg neural networks with nonlinear impulse. J Syst Sci Complex 23, 665–680 (2010). https://doi.org/10.1007/s11424-010-0151-x

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  • DOI: https://doi.org/10.1007/s11424-010-0151-x

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